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Natural products (NPs) continue to inform the discovery and development of a diversity of drugs, both marketed and investigational. Pain, one of the most common of human experiences and profound challenges in medicine and biology, has emerged at the core of an urgent societal problem, in the United States and globally. The present study employs a retrospective analysis of an extensive set of published literature curated in the NAPRALERT database to identify NPs with experimental evidence of bioactivity supporting the selection and prioritization of NP leads with promise in pain management. The NAPRALERT pain data set currently documents >38,000 pain-relevant experiments reported in >1,750 distinct journals. The evidence presented here was annotated from >10,000 distinct scientific publications identifying NP extracts and isolates with experimental biological data indicating positive mitigation of pain, inflammation, and/or modulation of nociceptive signaling targets. Correlation of ethnomedical uses with experimental data represents a value-added approach to the selection and prioritization of leads. Dissemination of this unique NP/pain data set, with experimental data and information applicable to basic, translational, and clinical science stakeholders alike, furnishes practical evidence in support of a rational selection of NPs for directed pain research. A large portion of the NAPRALERT pain-relevant data set, along with a set of query tools designed to assist user-directed selection and prioritization of leads, are presented as Supporting Information in order to mitigate the limitations inherent in presenting such a large data set in (print) format. To support user efforts, this report involves explication of NAPRALERT data organization and the articulation of rational approaches to user-guided selection of evidence-based NP leads.

Abstract from conference

NAPRALERT is a database on natural products, including data on ethnobotany, chemistry, pharmacology, toxicology, and clinical trials from literature dating back to the 19th century. Established in 1975 by Norman R. Farnsworth, it became a web accessible resource in 2005 but soon became stagnant while literature grew exponentially. After a complete rewrite of the platform, the focus is now on connecting this resource to the rest of the existing databases and expanding its usability. The creation of a Pharmacognosy/Natural Product ontology will foster better understanding of this domain, its linking potential with other resources and the ability to automatize literature annotation and entry efficiently.

NAPRALERT is a database on natural products, including data on the ethnobotany, chemistry, pharmacology, toxicology, and clinical trials. It was established in 1975 by the late Norman R. Farnsworth, at a time when computerized databases were just starting. It became web-accessible in 2005. Due to resource constraints, few enhancements were made to the existing database structure. Now, 10 years later, NAPRALERT faces the challenge of catching-up with other well-established resources.

High-throughput biology has contributed a wealth of data on chemicals, including natural products (NPs). Recently, attention was drawn to certain, predominantly synthetic, compounds that are responsible for disproportionate percentages of hits but are false actives. Spurious bioassay interference led to their designation as pan-assay interference compounds (PAINS). NPs lack comparable scrutiny, which this study aims to rectify. Systematic mining of 80+ years of the phytochemistry and biology literature, using the NAPRALERT database, revealed that only 39 compounds represent the NPs most reported by occurrence, activity, and distinct activity. Over 50% are not explained by phenomena known for synthetic libraries, and all had manifold ascribed bioactivities, designating them as invalid metabolic panaceas (IMPs). Cumulative distributions of ∼200,000 NPs uncovered that NP research follows power-law characteristics typical for behavioral phenomena. Projection into occurrence–bioactivity–effort space produces the hyperbolic black hole of NPs, where IMPs populate the high-effort base.

A recent article by Baell(1) on the problems experienced by medicinal chemists with pan-assay interference compounds (PAINS) and Shoichet’s work(2) on the impact of aggregation occurring in high throughput screening libraries, prompts a consideration of how these and other similar problems are experienced by pharmacognosists with promiscuous invalid metabolites as panaceas (PIMPs). Contrary to the classical definition of secondary metabolites as being species specific (or near specific), several natural products, particularly in the more extensively investigated plant kingdom, are common across species, genera, and even families (e.g. β-sitosterol). In the course of bioactivity-guided fractionation, PIMPs have shown up as major components in active fractions of a wide variety of pharmacological assays, i.e., they have been designated as panaceas. As in the case of PAINS, these assay results are almost invariably invalid and lead enthusiastic young scientists down a garden path. Why does this happen and how can it be avoided? Interestingly, the advances in modern methods of structure determination have exacerbated this problem, because it is possible to determine the structure of a compound when it is quite impure, and residual complexity is characteristic of chromatographic fractionation. That these residuals are often the source of the bioactivity is also frequently overlooked. Classic examples where this has occurred and ways to avoid it will be outlined.